R Notebook

library(plotly)

Loading required package: ggplot2
Registered S3 method overwritten by 'data.table':
  method           from
  print.data.table     
Registered S3 methods overwritten by 'htmltools':
  method               from         
  print.html           tools:rstudio
  print.shiny.tag      tools:rstudio
  print.shiny.tag.list tools:rstudio
Registered S3 method overwritten by 'htmlwidgets':
  method           from         
  print.htmlwidget tools:rstudio

Attaching package: ‘plotly’

The following object is masked from ‘package:ggplot2’:

    last_plot

The following object is masked from ‘package:stats’:

    filter

The following object is masked from ‘package:graphics’:

    layout

library(ggplot2)
library(readr)
library(dplyr)

Attaching package: ‘dplyr’

The following objects are masked from ‘package:stats’:

    filter, lag

The following objects are masked from ‘package:base’:

    intersect, setdiff, setequal, union

df <- read.csv('european_pop_gdp_per_capita.csv')
head(df)

 
plt <- ggplot(df, aes(x=population, y=gdp_per_capita)) + geom_point(aes(color=Country)) 

plt

pointsToLabel <- c("Austria", "Belgium", "Bulgaria", "Estonia", "France", "Germany", "Italy", "Netherlands", "Spain", "United Kingdom")

#plt2 <- plt + geom_text(aes(label = Country), color = "gray20", fontface='bold', data = subset(df, Country %in% pointsToLabel),check_overlap = TRUE)
plt2 <- plt + geom_text(aes(label = Country), color = "gray20", fontface='bold',check_overlap = TRUE)
plt2

plt3 <- plt2 + scale_x_continuous(name='Population', limits = c(0,90000000))
ggplotly(plt3)

Ok, so this looks pretty scrunched up, and it’s not a particularly useful graph (as I never really thought there was a relationship between population and GDP per capita). But it let me practise using some ggplot2 and plotly features, so it was a useful learning experience.